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Radiomics

Computational approach that extracts quantitative features from medical imaging to characterize tumor phenotypes and predict treatment outcomes.

Full Definition

Radiomics involves the high-throughput extraction of quantitative features from radiological images using specialized software algorithms, transforming imaging data into mineable information. These features can include tumor shape, texture, intensity patterns, and spatial relationships that may not be apparent to visual inspection. When combined with machine learning approaches, radiomic analysis can potentially predict treatment response, prognosis, and molecular characteristics of tumors non-invasively. The field represents an intersection of medical imaging, computer science, and oncology, with growing applications in personalized cancer care and treatment monitoring.

In Context

"Radiomics analysis of pre-treatment CT scans predicted response to immunotherapy with 78% accuracy." — Research publication
"The radiomics workflow included image segmentation, feature extraction, and machine learning model development." — Technical methods section

Also known as

radiomic analysis imaging biomarkers quantitative imaging

Contrasted with

qualitative imaging visual assessment

Don't confuse with

radiogenomics imaging informatics

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